Energy Conservation Behavior of Thai University Students
Bibliographic record
Abstract
An estimated 1.2 billion people, or 16% of the global population, did not have access to electricity in 2015. Therefore, access and the conservation of energy have become critical issues in a country’s quest for economic prowess and sustainability. This research, therefore, aimed to study the energy-conservation behavior of university students, and compare their energy-saving behavior categorized by gender and university group. The sample of 900 undergraduate students came from 15 Thai public universities under the Office of the Higher Education Commission [OHEC] in the 2013 academic year. The sample was randomly selected using a multi-stage sampling method. The instrument used to collect data in this research was a 5-level rating-scale questionnaire with reliability which was between 0.86-0.94. Data were analyzed using mean, standard deviation, t-test for independent sample and one-way ANOVA. The findings revealed that the students exhibited energy-conservation behavior in a family context at a high level, while energy-conservation behavior for themselves, and for the public was at a moderate level. Male and female students had different energy-conservation behaviors, and students under different university groups had distinct energy-conservation behaviors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".